Data Science

In the past two decades the diversity and production of big data and its accessibility have ballooned enormously, thereby creating new opportunities for insights about organizations and markets. Yet those opportunities cannot be fully realized without an understanding of the analytic strategies needed to approach the data, and what insights they can and cannot provide.

We understand that the real science in data sciences lies in the ability to transform the data into actionable information. It is a complex procedure that requires more than just the ability to capture, process, and visualize the data. Advances in computing infrastructure have led to an explosion in both the types and the quantity of data available, making data from traditional sources that required specialized equipment or privileged access (e.g., trading information, satellite data, social commentary from around the world), accessible instantly to almost everyone. The availability of big data enables us to ask different kinds of analytic questions—and to use different analytic methods to answer them. These questions can be used to identify a wide range of opportunities and/or threats to your organization.

Regardless of the type of data or their domain, we approach the big data problem by understanding the analytic questions that need to be asked and the existing operational analytic environment. Building on that understanding, we can help clients to optimize both the human and the technology strategies that work for them. Investments in analytic tools cannot be optimized without some improvement of the human and cognitive approach to using them.